Algorithms For Dummies

YOUR SECRET WEAPON TO UNDERSTANDING—AND USING!—ONE OF THE MOST POWERFUL INFLUENCES IN THE WORLD TODAY

From your Facebook News Feed to your most recent insurance premiums—even making toast!—algorithms play a role in virtually everything that happens in modern society and in your personal life. And while they can seem complicated from a distance, the reality is that, with a little help, anyone can understand—and even use—these powerful problem-solving tools!

In Algorithms For Dummies, you'll discover the basics of algorithms, including what they are, how they work, where you can find them (spoiler alert: everywhere!), who invented the most important ones in use today (a Greek philosopher is involved), and how to create them yourself.

You'll also find:

* Dozens of graphs and charts that help you understand the inner workings of algorithms
* Links to an online repository called GitHub for constant access to updated code
* Step-by-step instructions on how to use Google Colaboratory, a zero-setup coding environment that runs right from your browser

Whether you're a curious internet user wondering how Google seems to always know the right answer to your question or a beginning computer science student looking for a head start on your next class, Algorithms For Dummies is the can't-miss resource you've been waiting for.

JOHN MUELLER has published more than 100 books on technology, data, and programming. John has a website and blog where he writes articles on technology and offers assistance alongside his published books.

LUCA MASSARON is a data scientist specializing in insurance and finance. A Google Developer Expert in machine learning, he has been involved in quantitative analysis and algorithms since 2000. Introduction 1

PART 1: GETTING STARTED WITH ALGORITHMS 7

Chapter 1: Introducing Algorithms 9

Chapter 2: Considering Algorithm Design 23

Chapter 3: Working with Google Colab 41

Chapter 4: Performing Essential Data Manipulations Using Python 59

Chapter 5: Developing a Matrix Computation Class 79

PART 2: UNDERSTANDING THE NEED TO SORT AND SEARCH 97

Chapter 6: Structuring Data 99

Chapter 7: Arranging and Searching Data 117

PART 3: EXPLORING THE WORLD OF GRAPHS 139

Chapter 8: Understanding Graph Basics 141

Chapter 9: Reconnecting the Dots 161

Chapter 10: Discovering Graph Secrets 195

Chapter 11: Getting the Right Web page 207

PART 4: WRANGLING BIG DATA 223

Chapter 12: Managing Big Data 225

Chapter 13: Parallelizing Operations 249

Chapter 14: Compressing and Concealing Data 267

PART 5: CHALLENGING DIFFICULT PROBLEMS 289

Chapter 15: Working with Greedy Algorithms 291

Chapter 16: Relying on Dynamic Programming 307

Chapter 17: Using Randomized Algorithms 331

Chapter 18: Performing Local Search 349

Chapter 19: Employing Linear Programming 367

Chapter 20: Considering Heuristics 381

PART 6: THE PART OF TENS 401

Chapter 21: Ten Algorithms That Are Changing the World 403

Chapter 22: Ten Algorithmic Problems Yet to Solve 411

Index 417

ntroduction 1

PART 1: GETTING STARTED WITH ALGORITHMS 7

Chapter 1: Introducing Algorithms 9

Chapter 2: Considering Algorithm Design 23

Chapter 3: Working with Google Colab 41

Chapter 4: Performing Essential Data Manipulations Using Python 59

Chapter 5: Developing a Matrix Computation Class 79

PART 2: UNDERSTANDING THE NEED TO SORT AND SEARCH 97

Chapter 6: Structuring Data 99

Chapter 7: Arranging and Searching Data 117

PART 3: EXPLORING THE WORLD OF GRAPHS 139

Chapter 8: Understanding Graph Basics 141

Chapter 9: Reconnecting the Dots 161

Chapter 10: Discovering Graph Secrets 195

Chapter 11: Getting the Right Web page 207

PART 4: WRANGLING BIG DATA 223

Chapter 12: Managing Big Data 225

Chapter 13: Parallelizing Operations 249

Chapter 14: Compressing and Concealing Data 267

PART 5: CHALLENGING DIFFICULT PROBLEMS 289

Chapter 15: Working with Greedy Algorithms 291

Chapter 16: Relying on Dynamic Programming 307

Chapter 17: Using Randomized Algorithms 331

Chapter 18: Performing Local Search 349

Chapter 19: Employing Linear Programming 367

Chapter 20: Considering Heuristics 381

PART 6: THE PART OF TENS 401

Chapter 21: Ten Algorithms That Are Changing the World 403

Chapter 22: Ten Algorithmic Problems Yet to Solve 411

Index 417

ntroduction 1

PART 1: GETTING STARTED WITH ALGORITHMS 7

Chapter 1: Introducing Algorithms 9

Chapter 2: Considering Algorithm Design 23

Chapter 3: Working with Google Colab 41

Chapter 4: Performing Essential Data Manipulations Using Python 59

Chapter 5: Developing a Matrix Computation Class 79

PART 2: UNDERSTANDING THE NEED TO SORT AND SEARCH 97

Chapter 6: Structuring Data 99

Chapter 7: Arranging and Searching Data 117

PART 3: EXPLORING THE WORLD OF GRAPHS 139

Chapter 8: Understanding Graph Basics 141

Chapter 9: Reconnecting the Dots 161

Chapter 10: Discovering Graph Secrets 195

Chapter 11: Getting the Right Web page 207

PART 4: WRANGLING BIG DATA 223

Chapter 12: Managing Big Data 225

Chapter 13: Parallelizing Operations 249

Chapter 14: Compressing and Concealing Data 267

PART 5: CHALLENGING DIFFICULT PROBLEMS 289

Chapter 15: Working with Greedy Algorithms 291

Chapter 16: Relying on Dynamic Programming 307

Chapter 17: Using Randomized Algorithms 331

Chapter 18: Performing Local Search 349

Chapter 19: Employing Linear Programming 367

Chapter 20: Considering Heuristics 381

PART 6: THE PART OF TENS 401

Chapter 21: Ten Algorithms That Are Changing the World 403

Chapter 22: Ten Algorithmic Problems Yet to Solve 411

Index 417